similar to: Strange behaviour of spectrum()?

Hi, everyone, I tried to use "spectrum()" or "spec.pgram()" to get a periodogram of a time series but they didn't work. Even the examples given in the help file didn't work (all with the same error message, below). And the 'ts'ibrary was loaded with "library(ts)" or "library("ts"). I also tried library(tseries) but got the same problem.

Time Series functions in R ========================== I think a good basic S-like functionality for library(ts) in base R would include ts class, tsp, is.ts, as.ts plot methods start end window frequency cycle deltat lag diff aggregate filter spectrum, spec.pgram, spec.taper, cumulative periodogram, spec.ar? ar -- at least univariate by Yule-Walker arima -- sim, filter, mle, diag, forecast

Hi, I'm wondering why the spectrum() phase of quadrature couple isn't purely +/-pi. But mostly, I'm looking for a recommended way to take a 2-D spectrum and convert it into a single complex array. Kindly consider: # 10 Hz sine wave 10 seconds long sampled at 50 Hz deltaT = 1/50 t = seq(0, 10, deltaT) w = 2 * pi * 10 x = ts( sin( w * t ), deltat = deltaT ) y = ts( sin(

Hi All, I have two time series, each has length 354. I tried to calculate the coherency^2 between them, but the value I got is always 1. On a website, it says: " Note that if the ensemble averaging were to be omitted, the coherency (squared) would be 1, independent of the data". Does any of you know how to specify properly in R in order to get more useful coherency? The examples in

For the command 'spectrum' I read: The spectrum here is defined with scaling 1/frequency(x), following S-PLUS. This makes the spectral density a density over the range (-frequency(x)/2, +frequency(x)/2], whereas a more common scaling is 2? and range (-0.5, 0.5] (e.g., Bloomfield) or 1 and range (-?, ?]. Forgive my ignorance but I am having a hard time interpreting this. Does this mean

Hello. Does anyone know how to generate a power spectrum from the STFT function in package e1071? The output for this function supplies the Fourier coefficients, but I do not know how to relate these back to the power spectrum. Alternatively, if anyone is aware of other packages/functions that perform short time Fourier transforms, that would also be helpful. Thanks. -- View this message in

hi R users I have a large 1D dataset and some of them is NA value . I found I cound get the spectrum by such a command. ua=c£¨10£¬30 £¬40£¬50£¬NA£© spectrum(ua) and I could not use na.rm just like mean or sd function How could I get the spectrum of ua ? thank you . -- TANG Jie [[alternative HTML version deleted]]

Dear list, I apologies first for my English, hope you will understand well my question. I am working on 1/2 hour piezometric data, time unit is second. They present daily oscillation when using the spectrum() function. What I am really interested in, is to find the amplitude corresponding to this oscillation. I work with a college using Matlab, and although we apply the same methodology, our

I am reading some documentation about Cross Spectrum Analysis as a technique to compare spectra. My understanding is that it estimates the correlation strength between quasi-periodic structures embedded in two signals. I believe it may be useful for my signals analysis. I was referred to the R functions that implement this type of analysis. I tried all the examples which generated a series of

Fritz just put the first version of a new time series package to the contrib section at CRAN. The package is called "tseries.tgz" and provides a library for time series analysis. It contains acf Autocorrelation Function adf.test Augmented Dickey-Fuller Test amif Auto Mutual Information Function bds.test BDS Test

Fritz just put the first version of a new time series package to the contrib section at CRAN. The package is called "tseries.tgz" and provides a library for time series analysis. It contains acf Autocorrelation Function adf.test Augmented Dickey-Fuller Test amif Auto Mutual Information Function bds.test BDS Test

Dear R users I have two questions about estimating the spectral power of a time series: 1) I came across a funny thing with the following code: data(co2) par(mfrow=c(2,1)) co2.sp1<-spectrum(co2,detrend=T,demean=T,span=3) co2.sp2<-spectrum(co2[1:468],detrend=T,demean=T,span=3) The first plot displays the frequencies ranging from 0 to 6 whearas the second plot displays the same curve but

Hi everybody! I am searching for an R implementation of multi-scale singular spectrum analysis (SSA), which was introduced by Yiou etal (2000) (Data-adaptive wavelets and multi-scale singular-spectrum analysis) and further described in Ghil etal (2002). For SSA alone I found an package recently published on r-forge: http://r-forge.r-project.org/projects/simsalabim/ I am happy about any

Dear useRs, I have a curve which is a mixture of Gaussian curves (for example UV emission or absorption spectrum). Do you have any suggestions how to implement searching for optimal set of Gaussian peaks to fit the curve? I know that it is very complex problem, but maybe it is a possibility to do it? First supposement is to use a nls() with very large functions, and compare AIC value, but it is

This was an interesting post from another list I'm on. I think that with all of the echo cancellation discussion happening, that someone perhaps might be on the lookout for this type of software, so this post was well-timed for Asterisk uses. It is perhaps the case that those of you working on volume/echo/etc stuff might find this useful towards your goals. JT >To: [snip]

Hi, I've been using Speex in my voice-over-IP program on Win32, in wideband (16kHz) mode. I just starting using VBR recently and have run into something that might be a problem within Speex: If someone hasn't spoken for a little while, and the bitrate drops to very low, sometimes the high half of the spectrum becomes frozen with a looping sound. The bottom half of the spectrum is

Hi, I have a plot that is essentially the same as that in Figure 5.6 of "Lattice - Multivariate Data Visualization with R". The key difference is that I would like to add a title to top of the grey color spectrum legend, but have thus far been unsuccessful. I've tried a variety of options, but to no avail. I'm new to R, and admittedly I don't understand the

Jean-Marc Valin (jean-marc.valin@hermes.usherb.ca) wrote: > > > I've been using Speex in my voice-over-IP program on Win32, in > > wideband (16kHz) mode. I just starting using VBR recently and > > have run into something that might be a problem within Speex: > > Are you turning on DTX in addition to VBR? Also, what version are you > using. As of 1.0, DTX is

Reading Monty's message, I better re-post this one :-). In another thread the following was said: > It might help if you also mentioned that the sound quality of Ogg is > significantly better than MP3 (assuming that you use regular MP3, not > MP3Pro), especially at 32kbps. Speaking of which, would there be anything to stop Vorbis, maybe not v1 but in the future, to use similar

Hi R specialists, The na.omit.ts() method fails when the time series contains internal NA's. How can these automatically be removed? > spectrum(ts.mNDII, na.action=na.omit) Error in na.omit.ts(as.ts(x)) : time series contains internal NAs How can the na.action be activated correctly? > acf(ts.Lin, type=c("correlation"), na.action=na.omit) Error in na.omit.ts(as.ts(x)) :